01
Programming
Languages and frameworks I ship with
- Python
- SQL · T-SQL
- Java
- Bash
- REST APIs
- FastAPI
- Flask
- Data structures & algorithms
MLOps Engineer · California, USA
Sahith Aitha.
I build ML systems, data pipelines, cloud platforms and AI workflows that hold up in production.
HashiCorp Certified Terraform Associate & Google Cloud Professional Cloud Architect
02
About me
I build ML systems that hold up in production: messy data, strict reliability bars, real decisions on the line.
I'm an MLOps engineer who likes the unglamorous middle of machine learning. That's the part between a promising notebook and a model people can actually depend on. I've built survival and risk models for healthcare, heart-failure readmission models in research, cloud automation at Amazon, and the Linux and DevOps foundations underneath all of it.
Along the way I've published three peer-reviewed papers, serve on the Program Committee for ICTAI 2026, and won the 2026 Preston Ventures AI Hackathon with a Claude-powered agent system on AWS Bedrock. I work AI-augmented with Claude Code, and the judgment calls stay mine.
What excites me: AI systems that do real work reliably. Agents with clear verifiers, and pipelines that don't page you at 3am.
- 3peer-reviewed papers
- 3cloud & IaC certifications
- 12projects built
- 1stAI Hackathon 2026
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Skills & technologies
Verified badges on Credly
02
AI & machine learning
Modeling, evaluation and deep learning
- Survival analysis
- Predictive modeling
- Model evaluation
- PyTorch
- TensorFlow
- scikit-learn
- CNN · RNN · LSTM
- Generative AI
- OpenCV
03
MLOps
Taking models to production and keeping them healthy
- Kubernetes
- Docker
- Airflow
- MLflow
- GitHub Actions
- ArgoCD
- Prometheus
- Grafana
04
Cloud platforms
Where the systems run
- AWS EKS
- S3
- Lambda
- EC2
- DynamoDB
- Bedrock
- SageMaker
- Google Cloud
- Terraform
- AWS CDK
05
Data & databases
Pipelines, storage and data quality
- PostgreSQL
- BigQuery
- DynamoDB
- ETL pipelines
- Feature engineering
- OpenMetadata
- Data quality
06
Linux & systems
The foundations underneath
- RHEL administration
- Shell scripting
- Networking
- Performance tuning
- Puppet
- Git
- Distributed systems
04
Certifications
Google Cloud
Professional Cloud Architect
HashiCorp
Terraform Associate (003)
Oracle
OCI 2023 Certified Foundations Associate
05
Professional experience
-
– Present
MLOps Engineer
Preston Ventures, LLC · Aliso Viejo, CA
- Built a model evaluation suite (AUC, Brier Score, Integrated Brier Score) for survival and risk models, improving interpretability and decision confidence.
- Implemented data-quality monitoring across 30+ data assets with OpenMetadata and SQL validation checks, keeping training data consistent and catching drift.
- Automated the model lifecycle on AWS (EKS, S3, Lambda) with Airflow: continuous retraining, experiment tracking and reliable rollouts.
- Python
- SQL
- AWS
- Airflow
- OpenMetadata
-
–
MLOps Engineer
University of Cincinnati · Cincinnati, OH
- Designed and trained machine learning models that predict heart-failure readmissions, reaching 85% accuracy.
- Built ETL pipelines for the MIMIC-III dataset with PostgreSQL and BigQuery to clean, analyze and model large clinical data.
- Worked in Git and CI/CD workflows to move models from research toward deployment.
- Python
- PostgreSQL
- BigQuery
- scikit-learn
- CI/CD
-
–
Application Engineer
Amazon · Chennai, India
- Developed a real-time ticket-processing application that automatically detects and reports high-severity tickets, improving operational excellence by 15%.
- Implemented JSON data ingestion and storage in Amazon DynamoDB, working with cross-functional teams to ship it.
- Automated data parsing and emailed performance reports, so managers no longer had to review tickets one by one.
- Java
- AWS Lambda
- DynamoDB
- AWS CDK
-
–
Cloud & DevOps Engineer
EduSkills Foundation · Hyderabad, India
- Completed Red Hat RH124 and RH134, building hands-on RHEL administration, configuration, containerization and troubleshooting skills.
- Practiced Linux performance tuning and network configuration for production-style server environments.
- RHEL
- Linux
- Puppet
- AWS
-
–
Machine Learning Engineer
LinuxWorld Informatics Pvt. Ltd. · Jaipur, India
- Gained hands-on experience with machine learning, deep learning, DevOps and Linux.
- Built and Dockerized a deep-learning classification model for a real-world problem (Project Dhruvikaar).
- Python
- TensorFlow
- Docker
06
Education
–
Master of Science, Information Technology
University of Cincinnati · Cincinnati, OH
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Bachelor of Technology, Information Technology
Sreenidhi Institute of Science and Technology · Hyderabad, India
07
Projects
All repositories on GitHub- Flask app
- Prometheus
- Controller
- RL agent
IntelliScale
RL-driven cloud-native auto-scaling
A reinforcement-learning agent makes proactive scaling decisions from live CPU, memory and request-rate metrics, instead of reacting to fixed thresholds.
- Python
- FastAPI
- Docker
- Prometheus
- Grafana
- Train
- Docker
- GitHub Actions
- ArgoCD → K8s
AutoMLOps
Model-to-production MLOps pipeline
A model-agnostic template that trains, packages, deploys and monitors any ML model, with GitOps rollouts and live dashboards.
- scikit-learn
- FastAPI
- Kubernetes
- ArgoCD
- Grafana
- Terraform
- AWS EKS
- Docker Hub
- GitHub Actions
TeraKube
Cloud-native CI/CD on AWS
Provisions a VPC and EKS cluster with Terraform, then builds and deploys a containerized app through GitHub Actions, and tears everything down to keep costs at zero.
- Terraform
- AWS EKS
- Docker
- Kubernetes
- Street View
- S3
- ONNX on SageMaker
- JavaFX UI
CPASS
Cincinnati public transportation accessibility
Scores the accessibility of 3,000+ Cincinnati bus stops from 30,000 street-view images, detecting shelters, benches, signage and pavement conditions.
- Roboflow
- AWS SageMaker
- Python
- JavaFX
- MIMIC-III
- SQL
- Features
- Readmission model
Heart-failure readmission
Predictive analysis from EHR data
Predicts which heart-failure patients will be readmitted after discharge, giving clinicians earlier signals for care and hospital resource planning.
- Python
- SQL
- scikit-learn
- pandas
- EC2 metrics
- AWS CLI
- Clean
- LSTM forecast
Predictive cloud scaling
Machine learning for resource forecasting
Collects EC2 CPU and network metrics every hour and trains an LSTM to forecast utilization, so scaling can happen before demand arrives.
- Python
- LSTM
- AWS EC2
- Bash
More projects
- Emotion recognition through speech signalsLSTM-CNN on MFCC features (RAVDESS) · published
- Four-character CAPTCHA recognitionCNN computer-vision model · published
- Project DhruvikaarDockerized student-verification deep-learning model
- Potential to Sev2 NotifierHigh-severity ticket alerting at Amazon · write-up
- CI/CD with Jenkins on Kubernetes EngineJenkins pipelines on GKENo public repo
- Cloud Crafted: Kubernetes with TerraformGKE provisioned with TerraformNo public repo
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Let's build something that holds up.
Hiring for MLOps or ML platform work, or want to talk about a project? Send a note and I'll reply by email.